Programming Generative AI

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文件大小：4.03 GB
创建日期：2025-02-21
相关链接：ProgrammingGenerative

文件列表232

  •  Lesson 2 PyTorch for the Impatient/016. 2.15 Linear Regression with PyTorch.mp4  129.91 MB
  •  Lesson 6 Connecting Text and Images/016. 6.15 Playing with Prompts.mp4  120.71 MB
  •  Lesson 1 The What, Why, and How of Generative AI/009. 1.8 Introduction to Google Colab.mp4  115.35 MB
  •  Lesson 4 Demystifying Diffusion/005. 4.4 Generating Images with Diffusers Pipelines.mp4  97.61 MB
  •  Lesson 4 Demystifying Diffusion/006. 4.5 Deconstructing the Diffusion Process.mp4  81.29 MB
  •  Lesson 7 Post-Training Procedures for Diffusion Models/025. 7.24 Video-Driven Frame-by-Frame Generation with SDXL Turbo.mp4  78.73 MB
  •  Lesson 7 Post-Training Procedures for Diffusion Models/024. 7.23 Text-Guided Image-to-Image Translation.mp4  72.66 MB
  •  Lesson 7 Post-Training Procedures for Diffusion Models/018. 7.17 Depth and Edge-Guided Stable Diffusion with ControlNet.mp4  68.81 MB
  •  Lesson 1 The What, Why, and How of Generative AI/002. 1.1 Generative AI in the Wild.mp4  67.53 MB
  •  Lesson 4 Demystifying Diffusion/007. 4.6 Forward Process as Encoder.mp4  67.45 MB
  •  Lesson 7 Post-Training Procedures for Diffusion Models/004. 7.3 Quantitative Evaluation of Diffusion Models with Human Preference Predictors.mp4  63.47 MB
  •  Lesson 2 PyTorch for the Impatient/018. 2.17 Layers and Activations with torch.nn.mp4  62.29 MB
  •  Lesson 7 Post-Training Procedures for Diffusion Models/017. 7.16 Creating Edge and Depth Maps for Conditioning.mp4  58.39 MB
  •  Lesson 1 The What, Why, and How of Generative AI/006. 1.5 Formalizing Generative Models.mp4  56.96 MB
  •  Lesson 5 Generating and Encoding Text with Transformers/008. 5.7 Visualizing and Understanding Attention.mp4  56.29 MB
  •  Lesson 2 PyTorch for the Impatient/009. 2.8 Effortless Backpropagation with torch.autograd.mp4  55.79 MB
  •  Lesson 7 Post-Training Procedures for Diffusion Models/003. 7.2 Manual Evaluation of Stable Diffusion with DrawBench.mp4  54.21 MB
  •  Lesson 2 PyTorch for the Impatient/011. 2.10 Working with Devices.mp4  53.56 MB
  •  Lesson 5 Generating and Encoding Text with Transformers/009. 5.8 Turning Words into Vectors.mp4  51.75 MB
  •  Lesson 7 Post-Training Procedures for Diffusion Models/015. 7.14 Inference with Dreambooth to Create Personalized AI Avatars.mp4  51.16 MB
  •  Lesson 3 Latent Space Rules Everything Around Me/005. 3.4 Working with Images in Python.mp4  51.03 MB
  •  Lesson 4 Demystifying Diffusion/009. 4.8 Interpolating Diffusion Models.mp4  49.31 MB
  •  Lesson 1 The What, Why, and How of Generative AI/005. 1.4 How Machines Create.mp4  49.17 MB
  •  Lesson 5 Generating and Encoding Text with Transformers/004. 5.3 Generating Text with Transformers Pipelines.mp4  48.1 MB
  •  Lesson 7 Post-Training Procedures for Diffusion Models/014. 7.13 Dreambooth Fine-Tuning with Hugging Face.mp4  47.62 MB
  •  Lesson 2 PyTorch for the Impatient/019. 2.18 Multi-layer Feedforward Neural Networks (MLP).mp4  46.68 MB
  •  Lesson 7 Post-Training Procedures for Diffusion Models/008. 7.7 Parameter Efficient Fine-Tuning with LoRA.mp4  45.43 MB
  •  Lesson 5 Generating and Encoding Text with Transformers/002. 5.1 The Natural Language Processing Pipeline.mp4  44.54 MB
  •  Lesson 5 Generating and Encoding Text with Transformers/007. 5.6 Transformers are Just Latent Variable Models for Sequences.mp4  42.94 MB
  •  Lesson 7 Post-Training Procedures for Diffusion Models/010. 7.9 Inference with LoRAs for Style-Specific Generation.mp4  42.53 MB
  •  Lesson 1 The What, Why, and How of Generative AI/007. 1.6 Generative versus Discriminative Models.mp4  42.33 MB
  •  Lesson 1 The What, Why, and How of Generative AI/004. 1.3 Multitudes of Media.mp4  41.42 MB
  •  Lesson 6 Connecting Text and Images/005. 6.4 Embedding Text and Images with CLIP.mp4  41.24 MB
  •  Lesson 6 Connecting Text and Images/007. 6.6 Semantic Image Search with CLIP.mp4  40.9 MB
  •  Lesson 3 Latent Space Rules Everything Around Me/018. 3.17 Exploring Latent Space.mp4  40.63 MB
  •  Lesson 3 Latent Space Rules Everything Around Me/007. 3.6 Convolutional Neural Networks in PyTorch.mp4  40.25 MB
  •  Lesson 5 Generating and Encoding Text with Transformers/003. 5.2 Generative Models of Language.mp4  39.8 MB
  •  Lesson 2 PyTorch for the Impatient/006. 2.5 Tensors in PyTorch.mp4  38.73 MB
  •  Lesson 6 Connecting Text and Images/003. 6.2 Vision-Language Understanding.mp4  38.14 MB
  •  Lesson 4 Demystifying Diffusion/011. 4.10 Image Restoration and Enhancement.mp4  38.06 MB
  •  Lesson 6 Connecting Text and Images/012. 6.11 Stable Diffusion Deconstructed.mp4  37.8 MB
  •  Lesson 5 Generating and Encoding Text with Transformers/006. 5.5 Decoding Strategies.mp4  37.7 MB
  •  Lesson 7 Post-Training Procedures for Diffusion Models/023. 7.22 Comparing SDXL and SDXL Turbo.mp4  37.58 MB
  •  Lesson 3 Latent Space Rules Everything Around Me/019. 3.18 Latent Space Interpolation and Attribute Vectors.mp4  37.49 MB
  •  Lesson 2 PyTorch for the Impatient/003. 2.2 The PyTorch Layer Cake.mp4  36.72 MB
  •  Lesson 3 Latent Space Rules Everything Around Me/008. 3.7 Components of a Latent Variable Model (LVM).mp4  36.54 MB
  •  Lesson 7 Post-Training Procedures for Diffusion Models/019. 7.18 Understanding and Experimenting with ControlNet Parameters.mp4  35.82 MB
  •  Lesson 3 Latent Space Rules Everything Around Me/017. 3.16 Training a VAE with PyTorch.mp4  35.49 MB
  •  Lesson 3 Latent Space Rules Everything Around Me/002. 3.1 Representing Images as Tensors.mp4  35.04 MB
  •  Lesson 3 Latent Space Rules Everything Around Me/016. 3.15 Transforming an Autoencoder into a VAE.mp4  34.86 MB